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Relief Work

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Machine learning and phone data can improve targeting of humanitarian aid.

Nature
The COVID-19 pandemic has devastated many low- and middle-income countries, causing widespread food insecurity and a sharp decline in living standards. In response to this crisis, governments and humanitarian organizations worldwide have distributed ...

Quantifying social capital creation in post-disaster recovery aid in Indonesia: methodological innovation by an AI-based language model.

Disasters
Smooth interaction with a disaster-affected community can create and strengthen its social capital, leading to greater effectiveness in the provision of successful post-disaster recovery aid. To understand the relationship between the types of intera...

Using spatial video and deep learning for automated mapping of ground-level context in relief camps.

International journal of health geographics
BACKGROUND: The creation of relief camps following a disaster, conflict or other form of externality often generates additional health problems. The density of people in a highly stressed environment with questionable safe food and water access prese...

Ethical implications related to processing of personal data and artificial intelligence in humanitarian crises: a scoping review.

BMC medical ethics
BACKGROUND: Humanitarian organizations are rapidly expanding their use of data in the pursuit of operational gains in effectiveness and efficiency. Ethical risks, particularly from artificial intelligence (AI) data processing, are increasingly recogn...